Detection of elliptical particles in atomic force microscopy images

The aim of this project was to automatically detect and measure salient elliptical particles in atomic force microscopy (AFM) images. We proposed an automatic detection method that approximates the shapes of particles by ellipses. Its results were similar to results of expert manual detection.

Atomic force microscopy (AFM) imaging is utilized in physics for scanning material surfaces; the value of each pixel reflects the height of surface at corresponding coordinates. AFM images, however, contain significant level of noise, which impedes interpretation of acquired image data.
Each sample analyzed in our project consisted of approximately elliptical, similarly sized particles. Their shape and size was thus characterized by the average length and width of a statistically significant number of particles in the image.

Method

We proposed a method based on segmentation of salient particles by watershed transform and on approximation of their shapes by ellipses. The parameters of ellipses were computed from image moments; the major and minor axes provide robust estimates of the length and width of each particle, respectively.

Watershed segmentation of a blurred AFM image.

Approximation of segmented particles by ellipses.

Detection of distorted particles (red).

Particles significantly distorted by noise were excluded from measurements; the distortion was estimated as the difference of the surface within the approximating ellipse from its least squares approximation by a semi-ellipsoid.

Surface of a blurred AFM image.

Approximation of salient particles by ellipsoids.

Results

Performance of the proposed method was tested on AFM images of pyrroles, and compared with manual detection by an expert physicist. Results indicated that the automatic method could be used in place of the time-consuming manual detection.